BACK TO THE BASICS: Understanding Online conversations with Big Data, Sentiment Analysis, Concept Clouds, and Semantic Analysis

With the availability of resources online being limitless, Internet users’ each have their own unique browsing habits: visiting social media pages, shopping online, reading about a topic, etc. Naturally, internet users are also having conversations online; it is now easy for someone to voice their opinion online and be heard by thousands.

This begs the question: WHY SHOULD ANYONE CARE ABOUT THE OPINION OF INTERNET USERS?

To put things bluntly, the practical opportunities from a business standpoint are fantastic; online conversations are the equivalent of massive unbiased focus groups and can be leveraged to the benefit of a business.

Take for example Lenovo’s success story: after sifting through thousands upon thousands of online conversations (social media, blogs, forums, etc.), Lenovo created new products in response to the voice of the public. These new products achieved fantastic sales simply because they responded to customer needs that were previously unanswered.

We are now able to gather massive amount of data points (referred to as Big Data) and the ability to analyse them now propels companies to a whole new level of customer experience.

For further insights, we recommend our guide to leveraging your influencers: http://semeon.com/…/branding-technique-101-leveraging-your…/

 

BIG DATA, THE DIFFERENCES BETWEEN THE FISHING ROD AND THE FISHING NET

Gathering data for consumer behavior used to be time consuming and an expensive endeavor. Today, data can be collected en masse through various channels and networks available on the internet, hence the term Big Data.

WHY SHOULD ANYONE CARE ABOUT BIG DATA?

There are other important factors besides the obvious time and cost reductions that make Big Data attractive. For starters, the massive amount of data grants businesses the ability of gathering insights with statistical validity, meaning that the voice of consumers is correctly represented. Furthermore, gathering data that is already available online is different than asking for opinions; the data gathered is less likely to be bias, so the true emotions and opinions of consumers will be depicted.

For example, Hertz used to handle customer satisfaction surveys locally for all their 8600+ locations! Not only was it inefficient, but the insights gathered were unable to truly depict the needs, wants and behaviors of the customers because of the surveys being isolated from one another. By switching to Big Data, Hertz went from throwing 8600 small sized fishing nets with difficulty, to easily throwing 1 giant sized net + leveraging new customer data channels previously inaccessible. The value that Hertz received following the implementation of Big Data is easily in the millions.

For further insights, we recommend how big data is revolutionizing how Ad Agencies operate: http://semeon.com/blog/big-data-ad-agencies-giving-reason-to-gut-decisions/

 

BUILDING YOUR CONTENT CREATION STRATEGY WITH SENTIMENT ANALYSIS.

We’ve established that online conversations are pivotal for businesses to improve their customer experience. However, having to read every bit of conversations manually and extracting insights is humanly impossible. This is where sentiment analysis come into play.

Sentiment Analysis at its core is the process of analysing conversations and gauging the strength of the emotions behind them in an attempt at understanding a) if conversations are positive, negative or neutral, and b) what aspects of the conversation are positive, negative or neutral.

WHY SHOULD ANYONE CARE ABOUT THE EMOTIONS BEHIND CONVERSATIONS?

Sentiment Analysis is a fantastic way for companies to track their brand or products and understand how their consumers react. The main benefit from sentiment analysis alone is the ability to understand the reception of a brand or product in the face of change, for example: after a new product release or a marketing campaign.

The perfect example to highlight the strength of sentiment analysis would be Whole Food’s Asparagus Water situation. After releasing the product, customers were quick to express their discontent online. Had Whole Food implemented sentiment analysis, the whole Asparagus Water situation would have been killed. However, since they did not leveraging sentiment analysing, they were ridiculed by the media, continuously criticised by consumers and their stock dropped in the process until the product was removed.

For further insights, we recommend reading on the trends that are happening in social media analytics: http://semeon.com/blog/social-media-analytics-trends-in-2017/

 

CONCEPT CLOUDS AND SEMANTIC ANALYSIS, VIEWING THINGS CLEARLY

Powerful insights can now be automatically extracted by understanding the meanings of words and sentences of online conversations, assigning meanings to words be known as semantic analysis.

WHY SHOULD ANYONE CARE ABOUT SEMANTIC ANALYSIS?

While Semantic does a wonderful job assigning meanings the words and sentences, the perfect sidekick and the true hero in this story is contextual concepts cloud; the ability to portray and identify the driving forces that influence public opinion. Having the possibility of identifying the elements that bring value to customers, to observe what they care about and see the language they use, are fantastic ways of improving the customer experience.

When Apple released their Apple Watch, the company was keen on gathering the initial feedback from their users. Concept clouds were able to identify that the top concepts were “Apple” and “Watch”. This methodology offers little insights because no meanings can be placed after observing single words with no context. On the other hand, semantic analysis paired with context concept clouds was able to identify that the battery life in the apple watch was a problem that consumers cared about and something that they would want improvements on.

The ability to paint a full 360 degree view enables companies to attain new heights and identify opportunities that would have been impossible to observe without contextual concept clouds.

For further insights, we recommend understanding customers with the use of intent analysis: http://semeon.com/blog/intent-analytics-brings-real-insights-to-business-teams/

2 thoughts on “BACK TO THE BASICS: Understanding Online conversations with Big Data, Sentiment Analysis, Concept Clouds, and Semantic Analysis”

  1. Thank you for the sensible critique. Me & my neighbor were just preparing to do a little research about this. We got a grab a book from our local library but I think I learned more from this post. I’m very glad to see such excellent info being shared freely out there.

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